Saliency detection with bilateral absorbing markov chain guided by depth information

doi:10.3390/s21030838

CIOMP OpenIR

	Saliency detection with bilateral absorbing markov chain guided by depth information
	J. Wu; G. Han; P. Liu; H. Yang; H. Luo and Q. Li
	2021
发表期刊	Sensors (Switzerland)
ISSN	14248220
卷号	21 期号:3 页码:1-23
摘要	The effectiveness of depth information in saliency detection has been fully proved. How-ever, it is still worth exploring how to utilize the depth information more efficiently. Erroneous depth information may cause detection failure, while non-salient objects may be closer to the camera which also leads to erroneously emphasis on non-salient regions. Moreover, most of the existing RGB-D saliency detection models have poor robustness when the salient object touches the image boundaries. To mitigate these problems, we propose a multi-stage saliency detection model with the bilateral absorbing Markov chain guided by depth information. The proposed model progressively extracts the saliency cues with three level (low-, mid-, and high-level) stages. First, we generate low-level saliency cues by explicitly combining color and depth information. Then, we design a bilateral absorbing Markov chain to calculate mid-level saliency maps. In mid-level, to suppress boundary touch problem, we present the background seed screening mechanism (BSSM) for improving the construction of the two-layer sparse graph and better selecting background-based absorbing nodes. Furthermore, the cross-modal multi-graph learning model (CMLM) is designed to fully explore the intrinsic complementary relationship between color and depth information. Finally, to obtain a more highlighted and homogeneous saliency map in high-level, we structure a depth-guided optimization module which combines cellular automata and suppression-enhancement function pair. This optimization module refines the saliency map in color space and depth space, respectively. Comprehensive experiments on three challenging benchmark datasets demonstrate the effectiveness of our proposed method both qualitatively and quantitatively. 2021 by the authors. Licensee MDPI, Basel, Switzerland.
DOI	10.3390/s21030838
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收录类别	SCI ; EI
引用统计
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/65608
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	J. Wu,G. Han,P. Liu,et al. Saliency detection with bilateral absorbing markov chain guided by depth information[J]. Sensors (Switzerland),2021,21(3):1-23.
APA	J. Wu,G. Han,P. Liu,H. Yang,&H. Luo and Q. Li.(2021).Saliency detection with bilateral absorbing markov chain guided by depth information.Sensors (Switzerland),21(3),1-23.
MLA	J. Wu,et al."Saliency detection with bilateral absorbing markov chain guided by depth information".Sensors (Switzerland) 21.3(2021):1-23.

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